Image Super-Resolution (SR) is the process of reconstructing a High-Resolution (HR) image from one or a series of Low-Resolution (LR) images degraded by various artifacts such as aliasing, blurring, noise, and compression error. Video SR, by contrast, is the process of reconstructing a HR video from one or more LR videos in order to increase the spatial and/or temporal resolution(s). The spatial resolution of an imaging system depends on the spatial density of the detector (sensor) array and the point spread function (PSF) of the lens (optics). The temporal resolution, on the other hand, is influenced by the frame rate and exposure time of the camera. Spatial aliasing appears in images or video frames when the cut-off frequency of the detector is lower than that of the lens. Temporal aliasing happens in video sequences when the frame rate of the camera is not high enough to capture high frequencies caused by fast-moving objects. The blur in the captured images and videos is the overall effect of different sources such as defocus, motion blur, optical blur, and detector's blur induced by light integration within the active area of each detector in the array.